While every precaution has been taken in the preparation of this book, the publisher and author assume Downloading the Pig Package from Apache. To help you get started I've cataloged the 5 best books on Apache Pig and MapReduce. Some books are more beginner-friendly than others but they can all . Apr 17, Top 3 Apache Pig Books-Hadoop Pig books:Beginning Apache Pig for Beginners , Programming Pig is detailed book for Pig, Pig Design.
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Programming Pig: Dataflow Scripting with Hadoop: Computer Science Books @ roughnosecontdar.gq Learn to use Apache Pig to develop lightweight big data applications easily and quickly. This book shows you many optimization techniques and covers every. roughnosecontdar.gq: Apache Pig: Invent the future (): Ernesto Lee, Uzair Syed: Books.
Hadoop Operations by Eric Sammer.
This is the book if you need to know the ins and outs of prototyping, deploying, configuring, optimizing, and tweaking a production Hadoop system. Eric Sammer is a very knowledgeable engineer, so this book is chock full of goodies. Design Patterns is a great resource to get some insight into how to do non-trivial things with Hadoop.
This book goes into useful detail on how to design specific types of algorithms, outlines why they should be designed that way, and provides examples.
Hadoop in Action by Chuck Lam. It seems like this book provides a more gentle introduction to Hadoop compared to the other books in this list. Hadoop in Practice by Alex Holmes.
A slightly more advanced guide to running Hadoop. It includes chapters that detail how to best move data around, how to think in Map Reduce, and importantly how to debug and optimize your jobs. This A-Press book claims it will guide you through initial hadoop set up while also helping you avoid many of the pitfalls that usual Hadoop novices encounter.
Hadoop Essentials: A Quantitative Approach by Henry Liu. Another Hadoop intro book, Hadoop Essentials focuses on providing a more practical introduction to Hadoop which seems ideal for a CS classroom setting.
A book which aims to provide real-world examples of common hadoop problems. It also covers building integrated solutions using surrounding tools hive, pig, girafe, etc.
Enterprise Data Workflows with Cascading. This book includes all the top Pig development features that professionals use on a day-to-day basis. There are pages with 7 large chapters on data transformations, validations, and data reduction patterns with Pig. However, this book may be fairly simple or somewhat confusing, depending on your level of expertise.
Make sure that you have a good understanding of Hadoop and a basic understanding of Pig while learning through this book. This book is worth downloading just for the Pig source code. Here, every recipe has its own step-by-step approach so they all work like mini tutorials. In addition, it teaches you how to connect to different databases, how to connect with an AWS instance, and so much more.
So, this was all in Apache Pig Books.
Hope you like our explanation. However, we agree, this is a small list, but the ones listed here are definitely beneficial. Generate book count by year: This is the meat of the operation.
We first take group, which is an alias for the grouping value and say to place it in our new collection as an item named YearOfPublication.
We have the results, but how do we see them? What if we wanted to see books published per year by author? You can redefine it easily by following the above steps again. This will only keep records where we have a positive year of publication value. See the Pig Latin reference for a more detailed definition.
You may want to DUMP the pivot collection to see how the flattening works. This will find all author, year combinations. This nested structure lets us perform some extra steps before generation of values.